Forthcoming and Online First Articles

International Journal of Society Systems Science

International Journal of Society Systems Science (IJSSS)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Society Systems Science (3 papers in press)

Regular Issues

  • A Systematic Literature Review of Machine Learning Techniques in Financial Fraud Prevention and Detection   Order a copy of this article
    by Selorm Kofi Tagbo, Adebayo Felix Adekoya 
    Abstract: This review is aimed at analysing published articles in the field of fraud prevention and detection to determine the quantum of classification works that have been done using either supervised or unsupervised machine learning techniques. Again, by analysing these papers methodically, we would be able to identify the year that records the highest fraud publications and further rate continents based on the number of publications. Six hundred and sixty-two papers published in online databases like Scopus, Google Scholar, Web of Science, and Microsoft Academic between 2010 and 2022 were initially retrieved. Snowballing helped to discover more relevant articles. The search was inspired by PRISMA. Results showed that supervised machine learning technique was widely used as compared to the unsupervised learning counterpart. The number of publications in this field increased greatly between 2020 and 2021. Also, it was revealed that financial fraud cases within the African continent received the least attention from researchers.
    Keywords: machine learning; financial fraud; financial fraud detection; artificial intelligence.
    DOI: 10.1504/IJSSS.2023.10057287
     
  • A prototype for understanding the dynamics of invasion on empires   Order a copy of this article
    by Kishore Dutta, Dhritiman Talukdar 
    Abstract: In the evolution of every great empire of antiquity, the process of invasion was so inextricably interwoven that even the most powerful empire was incapable of escaping its barbarizing effect. A sudden invasion imposed major perturbation to a massive, centrally-organised system within a relatively shorter period and became a long-lasting destabilizing factor that brought drastic changes in the productivity, economy, manpower, and social order of the system. In order to understand such a vibrant dynamics as an interplay between competition and cooperation, here we show how a simple prototype can be constructed by taking into account some of the essential sociophysical processes in their simplest settings. The simulation of the model visualizes how the outcomes depend on factors such as the strength of the invaders, defensive manoeuvre of the empire and its internal configuration.
    Keywords: Competition and cooperation; centrally-organized system; historical processes; imperial invasion; computational model.

  • A Smart Prediction Model for Identifying Homeless People Using Machine Learning and Immediate Assistance System for Homeless People Using Android Application   Order a copy of this article
    by Md. Mehadi Hasan Shuvo, M. Hoq Chowdhury 
    Abstract: Homelessness is a state in which a person does not have access to an appropriate housing facility for living. The number of homeless people in developing countries like Bangladesh is on the rise. But due to a lack of proper prediction and assistance systems, they could not get the basic life needs they deserve. This paper focuses on gaining useful insights into why people are becoming homeless in our country and which criteria can be selected for identifying homeless people effectively. Based on the data from the survey this paper created a dataset for homeless people and applied five machine learning classifier algorithms to find out the best one for creating the prediction model for identifying homeless people. This paper also developed an Android Homeless People Aid application to provide immediate help to homeless people. The prediction model was also integrated into the application. The results highlight the usefulness of this work.
    Keywords: homelessness; machine learning; prediction model; Google Maps; Homeless People Aid; mobile application.
    DOI: 10.1504/IJSSS.2023.10058556
     

 

Return to top